SOTAVerified

Graph Embedding

Graph embeddings learn a mapping from a network to a vector space, while preserving relevant network properties.

( Image credit: GAT )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 981–990 of 1192 papers

TitleStatusHype
Dynamic Graph Representation Learning via Self-Attention NetworksCode0
Dynamic Graph Representation Learning with Fourier Temporal State EmbeddingCode0
DynG2G: An Efficient Stochastic Graph Embedding Method for Temporal GraphsCode0
EchoEA: Echo Information between Entities and Relations for Entity AlignmentCode0
Efficient Identity and Position Graph Embedding via Spectral-Based Random Feature AggregationCode0
Efficient Information Diffusion in Time-Varying Graphs through Deep Reinforcement LearningCode0
Efficiently Visualizing Large GraphsCode0
Efficient Parallel Translating Embedding For Knowledge GraphsCode0
Efficient Relation-aware Neighborhood Aggregation in Graph Neural Networks via Tensor DecompositionCode0
Ego-CNN: Distributed, Egocentric Representations of Graphs for Detecting Critical StructuresCode0
Show:102550
← PrevPage 99 of 120Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DeepGGEntropy Difference0—Unverified